Research talk: Automating and Optimizing IT Operations Management with AI
The vision of self-aware, self-healing, and self-managing Information Technology (IT) systems has remained elusive till recently. Recent advancements in Cloud computing, Natural Language Processing (NLP), Machine Learning (ML), and Artificial Intelligence (AI) in general, are…
Research talk: Breaking the deadly triad with a target network
The deadly triad refers to the instability of an off-policy reinforcement learning (RL) algorithm when it employs function approximation and bootstrapping simultaneously, and this is a major challenge in off-policy RL. Join PhD student Shangtong…
Panel: Challenges and opportunities of causality
What is causal machine learning? Is it the same as causality research? What are the recent advances and future opportunities? This panel is a unique session where you can hear world-leading researchers’ thoughts on causal…
Research talk: Focal Attention: Towards local-global interactions in vision transformers
At present, deep neural networks have become prevalent for building AI systems for vision, language and multimodality. However, how to build efficient and task-oriented models are still challenging problems for researchers. In these lightning talks,…
Keynote: Building a net-zero future together
At Microsoft, we fully believe the world needs to create a net-zero carbon economy by the year 2050. This is a broad problem—a truly planet-sized challenge—that the world needs to attack with a sense of…
Research talk: DARPA SafeDocs: an approach to secure parsing and information interchange formats
Speaker: Sergey Bratus, Program Manager, DARPA DARPA and MITRE estimate that 80 percent of software security vulnerabilities have incorrect input validation as their root cause. In such scenarios, attackers provide malformed input, which, when not…
Closing remarks: The Future of Privacy and Security
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit
Opening remarks: Reinforcement Learning
Reward-based learning has been a foundational component in human psychology. With reinforcement learning, researchers are using reward systems to accelerate AI, where techniques for gaming, robotics, and autonomous systems are being created with an emphasis…
Keynote: Key research challenges for real world reinforcement learning
Reinforcement learning has begun to have a broad impact on society with deployments and systems that make a real and tangible difference in how the world works. This is just scratching the surface though—in the…
Research talk: Resource-efficient learning for large pretrained models
At Microsoft Research, we are approaching large-scale AI from many different perspectives, which include not only creating new, bigger models, but also developing unique ways of optimizing AI models from training to deployment. One of…